Thursday, June 23, 2016

Improvements to ocean temperature measurements are making good measurements great

I have often said that global warming is really ocean warming.
As humans add more heat-trapping gases to the atmosphere, it causes the
Earth to gain energy. Almost all of that energy ends up in the oceans.
So, if you want to know how fast the Earth is warming, you have to
measure how fast the oceans are heating up.

Sounds easy enough at first, but when we recognize that the oceans
are vast (and deep) we can appreciate the difficulties.
How can we get
enough measurements, at enough locations, and enough depths, to measure
the oceans’ temperatures?
Not only that, but since climate change is a
long-term trend, it means we have to measure ocean temperature changes
over many years and decades.
We really want to know how fast the oceans’
temperatures are changing over long durations.

But that isn’t all.
Throughout the years, we have made changes to the
measurement methods.
From old canvas buckets that were dipped into
waters which were then measured, to insulated buckets, to temperature
probes on the hulls of ships, devices that would be dropped into deep
ocean waters, and now the ARGO fleet, which is approximately 3,000
autonomous devices that are more-or-less equally distributed across the
oceans.
Each of these devices measures temperatures a little
differently; they have biases.
As you change from one set of instruments
to another, you might see a cooling or warming effect related to the
change in instruments, not because the water temperatures are changing.
The seeming intractability of this problem is why I began studying it
a few years ago.
I have worked with colleagues to answer a very
specific equation related to one of the most commonly employed ocean
measurement devices, the eXpendable BathyThermograph (or XBT for short).
For many years, these devices formed the backbone of ocean temperature
measurements.
My colleagues and I want to ensure measurements from XBTs
are as accurate as possible.

UCI Marine Scientist Jim Nickels takes a second to show us some "Old School Science" equipment, -a Bathythermograph, and explain it's purpose.

These
devices are used by navies to measure the depth of the thermocline.
While that was their original mission, climate scientists have adopted
the devices for determining long-term ocean temperature changes.
The
problem is that the devices are relatively simple; they are freely
dropped into ocean waters.
As they descend, like a spinning torpedo,
they unwind a wire connected to a computer system on-board the ship.
A
sensor in the probe sends temperature information to the computer system
and a recording is made.
When the device expends its wire, the wire
breaks and the device continues to fall until it impacts the ocean
floor.

It’s important for scientists to know the depth of each temperature
measurement that the probe makes. The problem is, the probe does not
detect its depth.
Rather, its depth is estimated by knowing how fast the
probe falls in water.
The probe weight is balanced by drag forced
between the water and the device.
If the knowledge of probe speed is not
known accurately, it means a scientist may think the probe is at one
depth when in fact, it’s at a different depth.
This subtle uncertainty
can lead to large uncertainties in the overall ocean heat content.

Extensive experiments have shown that our expectations of probe speed
is suitable in areas where the ocean water is warm.
But, what about
Arctic regions?
There, where water is cold, the water has a higher
viscosity (and consequently drag force).
We wanted to know whether we
could correct that archive of ocean temperature measurements to account
for measurements made in cold waters.
To solve this problem, I teamed up
with world-class scientists Dr. Lijing Cheng and Rebecca Cowley.
Lijing
Cheng is a rapidly rising international scientist from the Chinese
Academy of Sciences.
He is currently producing some of the best research
on the Earth’s energy imbalance.
Rebecca Cowley is a data expert from CSIRO in Australia.
Her group is
recognized as among the best in ocean heat content measurements and
data quality.

Map of XBT lines

An eXpendable BathyThermograph (XBT) is a temperature probe that is dropped into the ocean from a ship, either by hand or using using an automatic launching system.

Temperatures are recorded as the probe drops at a known rate through about the upper kilometer of the ocean.

By making measurements at the same location at regular intervals, it is possible to observe the evolution of the thermal structure of the upper ocean.NOAA employs two sampling modes for deployment of XBT probes, each serving a different scientific purpose: Frequently Repeated (FR) and High Density (HD).

The article was just published by the American Society of Meteorology and can be found here.
Our data shows that as you move from warm waters to cold waters, probe
descent speed changes by approximately 2%.
We provided a simple way that
oceanographers could account for this effect in their data, and we then
compared our proposed correction to high-quality temperature data
obtained from side-by-side temperature experiments with two different
instruments.
We showed that our method reduces temperature error and
increases our understanding of ocean warming.
I asked Rebecca Cowley for her perspective on this study and she said,

We can see the effects of climate change in our oceans. To do
this, we measure changes in temperature in our oceans over decadal time
scales. Measuring the temperature of ocean water is not a new thing, it
has been done for hundreds of years, and over time, measurement
techniques have changed. In modern times, the XBT has been used
extensively to measure ocean temperature and is only one of many
methods. XBT data is special because it comprises ~50% of historical
data between 1967 and 2001, a huge resource for oceanographers and for
estimates of decadal changes in ocean temperature.Small biases in the historical XBT data have been identified and
various bias corrections have been developed which greatly improve the
XBT data for climate change estimates. This work focusses on a purely
physical method to estimate a fall rate for the XBT, which is unusual in
the field of bias correction estimates. By looking at the physical
shape of the XBT probe the fall rate is modelled. Other bias correction
studies have looked at comparisons between XBTs and other instruments. When we apply fall rate bias corrections, we improve the
historical XBT dataset (a massive resource), reduce the bias errors and
give estimates of ocean warming that are more comparable to the results
we see with other instrumentation. In turn, the XBT data becomes very
useful as it fills the gaps in time where we have very few other
instruments collecting ocean temperature data. The XBT data also becomes
useful for global ocean models – the data is included in the models and
it improves their accuracy. Improving the accuracy of our ocean models
leads to better forward estimates of future climate change impacts.

Sometimes science isn’t sexy.
Sometimes, you spend hours, days, and
weeks to create small improvements in data.
But at the end of the day,
these small improvements add up.
Being able to say we made things better
is one of the reasons we got into science in the first place.